Triple

T9318197
Position Surface form Disambiguated ID Type / Status
Subject Julia Domna E224175 entity
Predicate birthPlace P1 FINISHED
Object Emesa E302263 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Emesa | Statement: [Julia Domna, birthPlace, Emesa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Emesa
Context triple: [Julia Domna, birthPlace, Emesa]
  • A. Emesa chosen
    Emesa is the ancient name of the Syrian city now known as Homs, historically significant as a religious and trading center in Roman and early Christian times.
  • B. Eliada
    Eliada is a lesser-known biblical figure mentioned in the Old Testament as one of King David’s sons.
  • C. Almeirim
    Almeirim is a Portuguese city in the Ribatejo region, known for its agricultural traditions and its famous sopa da pedra (stone soup).
  • D. Huraymila
    Huraymila is a small town in central Saudi Arabia known for its traditional character and location within the greater Riyadh region.
  • E. Temara
    Temara is a coastal city in northwestern Morocco, situated just south of Rabat and known for its beaches and growing residential and industrial areas.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69ca8426d48481909596360f7791c7dd completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cd358b66148190a918c107490c8406 completed April 1, 2026, 3:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69d0c7c1fc848190bbb3ef6a1ed7a7d2 completed April 4, 2026, 8:11 a.m.
Created at: March 30, 2026, 7:38 p.m.